Undergraduate students

• Visit the Gina Cody SAS home page
• Get student request forms

• Course registration guide
• Class search
• Course schedules

No booking required! Join us for a meeting! 

Note: There will be no academic advising on Tuesday, February 21^st

In-person:

• Mon, Tue, Wed 9:30 - 12:00 & 14:00 - 16:30   (ER 10th floor) 

Online:

• Mon, Tue 10:00 - 11:00

Meeting URL: https://concordia-ca.zoom.us/s/85840596150

• Sections 71.70.1 & 71.70.2
• Honours Program section 71.70.4
• Extended Credit Program (ECP) section 71.70.3
• Mature Entry Program (MEP) section 14.2.3   

• Section 71.80
• Honours Program section 71.70.4
• Extended Credit Program (ECP) section 71.70.3
• Mature Entry Program (MEP) section 14.2.3

• Section 71.85
• Honours Program section 71.70.4
• Extended Credit Program (ECP) section 71.70.3
• Mature Entry Program (MEP) section 14.2.3

• Sections 71.75.1 & 71.75.2
• Extended Credit Program (ECP) section 71.75.3
• Mature Entry Program (MEP) section 14.2.3
• Honours Program section 71.75.4

Basic computer science skills are the perfect complement to any degree program at Concordia. The Minor in Computer Science is designed to meet the growing demand for computer-literate professionals, and may offer students more career opportunities after graduation.

• Section 71.70.5

• Computer science curriculum requirement letter
  (updated — July 2022)
• Computer science curriculum requirement letter
  (previous year — November 2020)

Honours option available in all Computer Science programs. Students may apply to the Honours program once they have completed 30 credits and have maintained a GPA of 3.00.

See section 71.70.4 of Undergraduate Calendar

• Honours program form

This is a one-credit project course set up to meet the special needs of certain students lacking one credit or less for graduation. It is a technical elective. Registration into this course requires the written permission from the Department of Computer Science and Software Engineering.

• Topic approval form (ENGR 411)

Students work on a computer science project under the supervision of a faculty member and submit a suitable written report on the work carried out.

• COMP 490/492 information and form

• Sections 71.70.8 & 71.70.9
• ECP Section 71.20.2
• MEP Section 14.2.3

• Software engineering curriculum requirement letter 
  (updated — July 2022)
• Software engineering curriculum requirement letter
  (previous years — November 2020)
  
• Software engineering curriculum requirement letter
  (previous years — May 2020)
  

This is a one-credit project course set up to meet the special needs of certain students lacking one credit or less for graduation. It is a technical elective. Registration into this course requires the written permission from the Department of Computer Science and Software Engineering.

• Topic approval form (ENGR 411)

This is a one-credit project course set up to meet the special needs of certain SOEN students lacking one credit or less for graduation. It is a technical elective. Registration into this course requires the written permission from the Department of Computer Science and Software Engineering.

• SOEN491 registration form

Computer Science 

General Electives must be chosen from the following lists*:

• Computer Science Electives found in § 71.70.2

• Mathematics Electives found in § 71.70.2

• General Education Electives found in § 71.110

• Basic and Natural Science Course list found in § 71.70.9

Software Engineering

Students must select three General Education elective credits from one of the three approved lists found in § 71.110*. These include Social Sciences, Humanities and Other Complementary Studies.  

Extended Credit Program (ECP) or Mature Entry Program (MEP):

Students in the Extended Credit Program (ECP) or the Mature Entry Program (MEP) (see §14.2.3) or any other students who have been assigned credits in Humanities and Social Sciences must select those credits from the Social Sciences and Humanities lists found in § 71.110*. Those credits cannot be chosen from the list of Other Complementary Studies list. 

ECP/MEP Elective credits may be chosen from the following lists: 

• Computer Science Electives found in § 71.70.2 (All three lists)

• Basic and Natural Science Course list found in § 71.70.9

   

Students wishing to take a course not listed in the degree requirements, must receive written permission from the Student Academic Services (SAS) Office of the Gina Cody School of Engineering and Computer Science prior to taking the course.

The contents of this course may vary from offering to offering. See below for course description and availability. 

Permission of the Department is generally required. 

FALL 2021: 

COMP 498 Neuroimage Computing (3 credits) – Section X

Prerequisites: ENGR 371 or COMP233. This course covers concepts, theories and practical knowledge in brain image processing and analysis. A practical introduction of medical imaging principles and image reconstruction will be provided. Topics to be covered include brain atlasing, computational anatomy, radiomics, tractography, image segmentation/classification, deep learning in neuroimaging, image-guided neurosurgery, and computer-assisted diagnosis. State-of-the-art software for neuroimage processing and analysis, as well as popular open source databases will also be covered through assignments and a project. Lectures: 3 hours per week.

WINTER 2023: Not Available

The contents of this course may vary from offering to offering. See below for course description and availability. 

Permission of the Department is generally required. 

WINTER 2023: Conversational Artificial Intelligence (4 credits)

COMP 499 Deep Learning (4 credits) – Section W

Prerequisite: COMP 432 (machine learning) or permission of the instructor.

This course introduces key concepts related to Conversation AI, covering both theoretical and practical aspects. The lectures will provide a general overview on modern conversational AI systems. The review covers basic machine learning concepts used in Conversational AI, including speech processing techniques. The course will address language models, which are an essential part of modern conversational AI methods. The course also covers higher-level methods such as spoken language understanding and dialogue systems. For each topic addressed during the lecture, a corresponding lab session allows students to familiarize themselves with the practical implementation of the techniques mentioned during the main lecture. The lectures are designed to provide a complete overview of the field of Conversational. A project is required.

Component(s): Lecture 3 hours per week;
Laboratory 2 hours per week

The contents of this course may vary from offering to offering. See below for course description and availability. 

Permission of the Department is generally required. 

WINTER 2023: Not Available 

The contents of this course may vary from offering to offering. See below for course description and availability. 

Permission of the Department is generally required. 

WINTER 2023: Not Available